The Evolution of Artificial Intelligence Enhanced Enterprise Resource Planning in Higher Education: A Comprehensive Meta-Data Analysis

The integration of Machine Learning (ML) and Artificial Intelligence (AI) into Enterprise Resource Planning (ERP) systems has become a key component in higher education, fostering operational efficiency and data-driven decision-making. This study examines a comprehensive meta-data analysis of research on AI-enhanced ERP systems in higher education, based on data from Google Scholar, ResearchGate, and arXiv from 2016 to 2024. 1136 relevant studies were identified and analyzed to uncover trends, thematic areas, and geographical distribution of research activity in this domain. Our analysis highlights the significant developments in implementing AI and Machine Learning (ML) in ERP systems, focusing on their impact on administrative processes, academic performance monitoring, and personalized learning experiences. Geographically, the findings reveal significant research in North America, Europe, and Asia, indicating regional advancements and priorities in educational technology. Thematic analysis identified emerging trends, including predictive analytics, intelligent resource allocation, and AI integration with cloud-based ERP systems. This study examines the current state of AI-enhanced ERP research and its practical implications for policy development in higher education institutions. It identifies critical weaknesses in existing literature, such as limited focus on developing nations and the ethical implications of AI deployment in ERP systems. This meta-data analysis provides a roadmap for future research and innovation in AI-driven ERP solutions, ensuring their alignment with the evolving needs of higher education. This study aims to guide researchers, educators, and policymakers in leveraging AI and ERP technologies to create more adaptive, efficient, and equitable educational environments.